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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,801 records · Page 100
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Influence of freeze-thaw cycles on capillary absorption and chloride penetration into concrete

Combined mechanical and environmental actions reduce service life of reinforced concrete structures more than each of the participating actions alone. In this contribution, the influence of freeze-thaw cycles on capillary water absorption and chloride penetration into ordinary concrete with two different water-cement ratios and air-entrained concrete was investigated. Water profiles in concrete were quantified by neutron radiography. Capillary water absorption and chloride penetration are both slowed down considerably by air entrainment. Chloride ions dissolved in water are filtered out of the penetrating salt solution and remain concentrated near the surface. Capillary water absorption and chloride penetration into ordinary concrete are accelerated considerably by frost damage. After exposure to freeze-thaw cycles a damage gradient from the surface to the center of the samples was observed. Transport mechanisms were studied in some detail and the data obtained can serve as a basis for more realistic prediction of service life of reinforced concrete structures under the influence of combined freeze-thaw cycles and chloride penetration.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Molecular-level insights into structure and dynamics in ionic liquids and polymer gel electrolytes

We report designing new electrolytes requires a better understanding of the correlation between their transport properties and their molecular structure. In this work, we present a detailed study of ionic liquids and polymer gel electrolytes probing their structure and dynamics by nuclear magnetic resonance (NMR) spectroscopy. In particular, ammonium- and phosphonium-based ionic liquids (ILs) are combined with different LiTFSI concentrations, and then with different ratios of poly(methylmethacrylate) polymer. The temperature dependence of self-diffusion coefficients of mobile species, D Li+ , D TFSI- and D P4441+ or D N4441+ , measured by pulsed field gradient (PFG) NMR spectroscopy obeys the Arrhenius equation. Diffusivity of [P4441][TFSI] ILs is found to be greater than those of the [N4441][TFSI] ILs in both liquid and gel electrolytes. Solid state NMR experiments including 13 C and 19 F MAS, 13 C{ 19 F}, 13 C{ 1 H} CPMAS probe the local structure and molecular-level interactions between ions and polymer in gel electrolytes, particularly for samples with higher PMMA content (≥25 wt%). Finally, the fast field cycling relaxometry has been used to unveil the rotational and translational dynamics of P4441 + or N4441 + and TFSI - by measuring 1 H and 19 F R 1 relaxation rate profiles at different temperatures. A comprehensive NMR analysis including relaxation studies at low magnetic field provides decisive new insights regarding the formation of ionic clusters and the interaction of ions with the polymer chain in the case of the gel electrolytes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Investigation of structural, electronic, elastic and optical properties of Cd{sub 1-x-y}Zn{sub x}Hg{sub y}Te alloys

Structural, optical and electronic properties and elastic constants of Cd1{sub -x-y}Zn{sub x} Hg{sub y}Te alloys have been studied by employing the commercial code Castep based on density functional theory. The generalized gradient approximation and local density approximation were utilized as exchange correlation. Using elastic constants for compounds, bulk modulus, band gap, Fermi energy and Kramers–Kronig relations, dielectric constants and the refractive index have been found through calculations. Apart from these, X-ray measurements revealed elastic constants and Vegard’s law. It is seen that results obtained from theory and experiments are all in agreement.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Linear convergence of accelerated conditional gradient algorithms in spaces of measures

A class of generalized conditional gradient algorithms for the solution of optimization problem in spaces of Radon measures is presented. The method iteratively inserts additional Dirac-delta functions and optimizes the corresponding coefficients. Under general assumptions, a sub-linear [see formula in PDF] rate in the objective functional is obtained, which is sharp in most cases. To improve efficiency, one can fully resolve the finite-dimensional subproblems occurring in each iteration of the method. We provide an analysis for the resulting procedure: under a structural assumption on the optimal solution, a linear [see formula in PDF] convergence rate is obtained locally.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1983

A study of the effects of Lebu devices on turbulent boundary layer drag

Initial measurements of the changes in local skin friction, velocity profile shape, and turbulence structure which result from the placement of tandem plates parallel to the wall in the outer region of thick turbulent boundary layers were made. Using a tunnel with a .75 m x 1.2 m x 7.3 m test section, which diverged so as to keep the pressure gradient less than 2x1000/ft, on the test wall, a skin friction reduction of approximately 30% was measured at xi/h = 62. This relaxed to a reduction of approximately 16% at xi/h = 124 for h/delta M = .6. The c sub f measurements for both the normal and modified boundary layers were obtained by measuring the slope of the velocity profile within the linear sublayer. Visual results indicated a continued presence of strong large eddy structure downstream of the devices. Local skin friction reduction of 12% at xi/h = 62 was also obtained with the manipulators above the boundary layer at y/delta m = 1.1.

Falco, R. E.↗
DOE OSTI2023

Prediction and Validation of Flow Properties in Porous Lattice Structures

High-porosity metal foams have been extensively studied as an attractive candidate for efficient and compact heat exchanger design. With the advancements in additive manufacturing, such foams can be manufactured with controlled topology to yield highly tailorable mechanical and transport properties. In this study, a lattice Boltzmann method (LBM)-based pore-scale model is implemented to simulate the fluid flow in additively manufactured (AM) metal foams with unit cell topologies of Cube, Face Diagonal (FD)-Cube, Tetrakaidecahedron (TKD), and Octet lattices. The pressure gradient versus average velocity profiles predicted by the LBM model were validated against in-house measurements on the AM lattice samples with the same unit cell topologies. Based on the simulation results, a novel hybrid model is proposed to accurately predict the volume averaged flow properties (permeability and inertial coefficients) of the four structures. Specifically, the linear LBM (neglecting inertial forces) is first implemented to obtain the intrinsic permeability, and then the standard LBM is applied to obtain the inertial coefficient. Convenient correlations for those flow properties as a function of porosity and fiber diameter are constructed. The effects of the AM print qualities on the flow properties are also discussed. The advantages of the hybrid model compared to the polynomial fitting approach for determining flow properties are discussed and compared quantitatively. The hybrid model and presented results are valuable for flow and thermal transport evaluation when designing new metal foams for specific applications and with different materials and topologies. Finally, the presented correlations based on pore-scale simulations can also be conveniently used in volume-averaged models to predict the macroscale flow behavior in such complex structures.

42 ENGINEERING↗
DOE OSTI2024

Detonation structure in the presence of mixture stratification using reaction-resolved simulations

Many investigations of detonation-based combustors have identified reactant mixture inhomogeneity as having a leading-order impact on wave dynamics and combustion efficiency. To examine this phenomenon in a simplified context, an array of two- and three-dimensional channel detonation simulations are conducted in the present work. The reactant mixture consists of stratified fuel and air, wherein the randomly distributed equivalence ratio field features a characteristic stratification length scale. Detailed chemical kinetics are implemented in an adaptive mesh refinement solution framework where the region near the shock front is resolved with Ο (100) cells per representative ZND induction length. The results show that in comparison to baseline cases with uniform reactant mixtures, reactant stratification has a marked impact on the detonation structure. Increasing the stratification length scale increases the size and irregularity of the detonation cells, yielding larger variations in wave speed. Triple point collisions in fuel-rich regions lead to local wave speeds above the notional mean CJ speed, but wave passage through inert regions causes the local wave speed and strength to diminish. Further, conditional statistics show that increasing the stratification length scale increases the variance in pressure and temperature in the primary reaction zone, as well as the variance in heat release over a range of mixture conditions. In addition to the reactant mixture, the impact of the boundary condition behind the detonation is also investigated. The results show that an inflow boundary condition acts to over-drive the wave, leading to higher peak pressures, smaller detonation cells, and increased reactant consumption. On the other hand, cases with a wall behind the wave exhibit weaker waves with lower peak pressures and heat release rates, as well as greater variance in conditional quantities. Comparisons between complementary two- and three-dimensional simulations show reasonable qualitative agreement in wave structure, speed, and conditional statistics.

42 ENGINEERING↗
DOE OSTI2018

Altered myofilament structure and function in dogs with Duchenne muscular dystrophy cardiomyopathy

Aim Duchenne Muscular Dystrophy (DMD) is associated with progressive depressed left ventricular (LV) function. However, DMD effects on myofilament structure and function are poorly understood. Golden Retriever Muscular Dystrophy (GRMD) is a dog model of DMD recapitulating the human form of DMD. Objective The objective of this study is to evaluate myofilament structure and function alterations in GRMD model with spontaneous cardiac failure. Methods and results We have employed synchrotron X-rays diffraction to evaluate myofilament lattice spacing at various sarcomere lengths (SL) on permeabilized LV myocardium. We found a negative correlation between SL and lattice spacing in both sub-epicardium (EPI) and sub-endocardium (ENDO) LV layers in control dog hearts. In the ENDO of GRMD hearts this correlation is steeper due to higher lattice spacing at short SL (1.9 μm). Furthermore, cross-bridge cycling indexed by the kinetics of tension redevelopment (ktr) was faster in ENDO GRMD myofilaments at short SL. We measured post-translational modifications of key regulatory contractile proteins. S-glutathionylation of cardiac Myosin Binding Protein-C (cMyBP-C) was unchanged and PKA dependent phosphorylation of the cMyBP-C was significantly reduced in GRMD ENDO tissue and more modestly in EPI tissue. Conclusions We found a gradient of contractility in control dogs' myocardium that spreads across the LV wall, negatively correlated with myofilament lattice spacing. Chronic stress induced by dystrophin deficiency leads to heart failure that is tightly associated with regional structural changes indexed by increased myofilament lattice spacing, reduced phosphorylation of regulatory proteins and altered myofilament contractile properties in GRMD dogs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Distributed and communication-efficient solutions to linear equations with special sparse structure

In this paper we report two distributed and communication-efficient algorithms based on the multi-agent system are proposed to solve a system of linear equations with the Laplacian sparse system matrix. One algorithm is based on the gradient descent method in optimization. In this algorithm, the agents only share partial information instead of all of their collective state vectors to save significant communication. The other algorithm is obtained by approximating Newton’s method for a faster convergence rate. Although it requires twice as much communication as the first one, it is still communication-efficient given the low dimension of the information shared among agents. The convergence at a linear rate is proved for both algorithms, and a comprehensive comparison of their convergence rate, communication burden, and computation costs is also performed. The proposed algorithms can be applied to various systems to solve those problems that can be modeled as a system of linear equations with a Laplacian sparse system matrix. Simulation results with the electric power system illustrate their effectiveness.

42 ENGINEERING↗
DOE OSTI2016

Structural, elastic and vibrational properties of ScGa{sub 3}

We have presented theoretical investigations of the atomic, elastic and lattice dynamical properties of ScGa{sub 3} using an ab-initio pseudopotential method and a linear response scheme, within the generalized gradient approximation. The calculated atomic parameters and elastic constants are in agreement with previous ab initio calculations and experimental measurements. The material shows ductile behavior. Full phonon dispersions for this material are reported.

36 MATERIALS SCIENCE↗
NASA NTRS1985

Modeling gravity and magnetic fields for crustal and upper mantle structures

Research was conducted to: (1) make a direct comparison between the gravity and magnetic fields near the ellipsoid and at the height expected for the Geopotential Research Mission (GRM) for the same geologic model, (2) obtain realistic estimates of the gradients that can be expected at the orbit height of the GRM, and (3) demonstrate the value of data that the GRM could provide for investigating upper mantle and deep crustal anomalies.

Denoyer, J. M.↗
NASA NTRS2009

Computer Code for Nanostructure Simulation

Due to their small size, nanostructures can have stress and thermal gradients that are larger than any macroscopic analogue. These gradients can lead to specific regions that are susceptible to failure via processes such as plastic deformation by dislocation emission, chemical debonding, and interfacial alloying. A program has been developed that rigorously simulates and predicts optoelectronic properties of nanostructures of virtually any geometrical complexity and material composition. It can be used in simulations of energy level structure, wave functions, density of states of spatially configured phonon-coupled electrons, excitons in quantum dots, quantum rings, quantum ring complexes, and more. The code can be used to calculate stress distributions and thermal transport properties for a variety of nanostructures and interfaces, transport and scattering at nanoscale interfaces and surfaces under various stress states, and alloy compositional gradients. The code allows users to perform modeling of charge transport processes through quantum-dot (QD) arrays as functions of inter-dot distance, array order versus disorder, QD orientation, shape, size, and chemical composition for applications in photovoltaics and physical properties of QD-based biochemical sensors. The code can be used to study the hot exciton formation/relation dynamics in arrays of QDs of different shapes and sizes at different temperatures. It also can be used to understand the relation among the deposition parameters and inherent stresses, strain deformation, heat flow, and failure of nanostructures.

Filikhin, Igor↗
DOE OSTI2020

Machine learning-based prediction of enzyme substrate scope: Application to bacterial nitrilases

Predicting the range of substrates accepted by an enzyme from its amino acid sequence is challenging. Although sequenc- and structure-based annotation approaches are often accurate for predicting broad categories of substrate specificity, they generally cannot predict which specific molecules will be accepted as substrates for a given enzyme, particularly within a class of closely related molecules. Combining targeted experimental activity data with structural modeling, ligand docking, and physicochemical properties of proteins and ligands with various machine learning models provides complementary information that can lead to accurate predictions of substrate scope for related enzymes. Here we describe such an approach that can predict the substrate scope of bacterial nitrilases, which catalyze the hydrolysis of nitrile compounds to the corresponding carboxylic acids and ammonia. Each of the four machine learning models (logistic regression, random forest, gradient-boosted decision trees, and support vector machines) performed similarly (average ROC = 0.9, average accuracy = ~82%) for predicting substrate scope for this dataset, although random forest offers some advantages. Finally, this approach is intended to be highly modular with respect to physicochemical property calculations and software used for structural modeling and docking.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

NbTi_BCC_SolidSolution_128atoms_VASP6

We performed density functional theory (DFT) calculations for body-centered-cubic (BCC) structures with 128 lattices sites of solid solution binary alloys niobium-titanium (Nb-Ti). The electronic structures of alloys have been calculated using Vienna Ab initio Simulation Package (VASP), https://github.com/ORNL/ScalableWorkflow_VASP_Calculations. Within this package the DFT approach is used to reduce many-body Schrodinger equation to set of single particle Kohn-Sham (KS) equations. The generalized electronic exchange-correlation functional is described by generalized gradient approximation with the Perdew-Burke-Ernzerhof parametrization. The electron-ion interactions is described by pseudopotentials developed within the plane-wave basis projector augmented-wave (PAW) approach. These pseudopotentials are available at the VASP portal (http://cms.mpi.univie.ac.at/vasp/). Our calculations have been run with the pseudopotentials treating s and p semi-core states as valence in case for the elements Nb and Ti. The electronic densities and potentials are expanded over plane-waves with energy cutoff of 350 eV. 2x2x2 k-mesh and normal precision were used. The alloys were modeled by supercell containing 128 randomly distributed atoms. At initial step the atoms occupy perfect bcc lattice cites. This initial structure was optimized until energy changes less than 1e-6 eV, while forces acting on atoms don't exceed 1e-2 eV/angstrom. The electron-ion interaction is described by PAW pseudopotentials. The calculations have been collected by sampling chemical compositions across the entire compositional range. The chemical compositions have been sampled by progressively changing the number of atoms per constituent by 4. For each chemical composition of binaries and ternaries, the first-principle calculations have been run for 100 randomized arrangements of the constituents on the BCC lattice sites. We collected data for a total of 3,100 randomized atomic structures over 31 chemical compositions. The calculations have been collected on Air Force HPC11 cluster using the VASP 6.5.1. Additional methodology and file structure information is available in the dataset README.txt file.

36 MATERIALS SCIENCE↗
NASA NTRS1993

Extending substructure based iterative solvers to multiple load and repeated analyses

Direct solvers currently dominate commercial finite element structural software, but do not scale well in the fine granularity regime targeted by emerging parallel processors. Substructure based iterative solvers--often called also domain decomposition algorithms--lend themselves better to parallel processing, but must overcome several obstacles before earning their place in general purpose structural analysis programs. One such obstacle is the solution of systems with many or repeated right hand sides. Such systems arise, for example, in multiple load static analyses and in implicit linear dynamics computations. Direct solvers are well-suited for these problems because after the system matrix has been factored, the multiple or repeated solutions can be obtained through relatively inexpensive forward and backward substitutions. On the other hand, iterative solvers in general are ill-suited for these problems because they often must restart from scratch for every different right hand side. In this paper, we present a methodology for extending the range of applications of domain decomposition methods to problems with multiple or repeated right hand sides. Basically, we formulate the overall problem as a series of minimization problems over K-orthogonal and supplementary subspaces, and tailor the preconditioned conjugate gradient algorithm to solve them efficiently. The resulting solution method is scalable, whereas direct factorization schemes and forward and backward substitution algorithms are not. We illustrate the proposed methodology with the solution of static and dynamic structural problems, and highlight its potential to outperform forward and backward substitutions on parallel computers. As an example, we show that for a linear structural dynamics problem with 11640 degrees of freedom, every time-step beyond time-step 15 is solved in a single iteration and consumes 1.0 second on a 32 processor iPSC-860 system; for the same problem and the same parallel processor, a pair of forward/backward substitutions at each step consumes 15.0 seconds.

Farhat, Charbel↗
DOE OSTI2019

Vectoring into Potential Blind Geothermal Systems in the Granite Springs Valley Area, Western Nevada: Application of the Play Fairway Analysis at Multiple Scales

The Great Basin region of the western USA is capable of generating much greater amounts of geothermal energy than currently produced. Most geothermal resources in this region are blind, and thus the favorable characteristics for geothermal activity must be synthesized and methodologies developed to discover new commercial-grade systems. The geothermal play fairway concept involves integration of multiple parameters indicative of geothermal activity as a means of identifying promising areas for new development. In the Nevada play fairway project, nine geologic, geochemical, and geophysical parameters were initially synthesized to produce a new geothermal potential map of 96,000 km2. Granite Springs Valley in western Nevada is a particularly promising site selected for detailed study. It contains several favorable structural settings, including terminations of major Quaternary normal faults and fault intersections. Geologic, geophysical, and geochemical techniques were employed to define the most likely sites for high permeability and select drilling targets for temperature-gradient holes. Local and intermediate permeability models were revised to reflect results of detailed analyses and generate new detailed play fairway maps of the area. The most promising site lies in the northeastern part of the basin directly east of Adobe Flat, where the horse-tailing termination of a major normal fault (as revealed by new gravity data), opaline sinter deposits, warm shallow wells, and a low-resistivity anomaly are collocated. Geothermometry suggests a blind system with temperatures as high as ~130°C in this area. Four new temperature-gradient holes document temperatures of ~80°C at ~150 m depth. Lessons learned in the detailed studies of this project include: 1) initially identified sites commonly include multiple favorable settings at a finer scale; 2) promising sites in Cenozoic basins cannot be well defined without detailed geophysical surveys; and 3) play fairway analysis is critical at multiple scales, providing a means to select regional prospects as well as vectoring into drilling targets at individual sites.

15 GEOTHERMAL ENERGY↗
NASA NTRS1984

Magnetopause structure and the question of particle accessibility

A simple plane model of the magnetopause is used to address the question of particle accessibility. Particle motion in the current sheet region is analyzed, showing that the concept of gyromotion is useful even when the electric and magnetic fields vary significantly over the gyroradius, as long as the variation is perpendicular to the drift direction. The first adiabatic invariant for particle motion is defined in such a way that it is preserved in regions of large field gradients, provided that the gradients are in a direction primarily perpendicular to the particle drifts. This generalized invariant provides an adiabatically conserved quantity that can be used to characterize particles as they move from a source region through the drift region and into the magnetopause itself, helping to resolve the accessibility question. Some preliminary results are given for the magnetopause structure based on the location of particle guiding points.

Whipple, E. C.↗
DOE OSTI2025

Harnessing Machine Learning to Predict MoS 2 Solid Lubricant Performance

Physical vapor deposited (PVD) molybdenum disulfide (MoS 2 ) solid lubricant coatings are an exemplar material system for machine learning methods due to small changes in process variables often causing large variations in microstructure and mechanical/tribological properties. Here, in this work, a gradient boosted regression tree machine learning method is applied to an existing experimental data set containing process, microstructure, and property information to create deeper insights into the process-structure–property relationships for molybdenum disulfide (MoS 2 ) solid lubricant coatings. The optimized and cross-validated models show good predictive capabilities for density, reduced modulus, hardness, wear rate, and initial coefficients of friction. The contribution of individual deposition variables (i.e., argon pressure, deposition power, target conditioning) on coating properties is highlighted through feature importance. The process-property relationships established herein show linear and non-linear relationships and highlight the influence of uncontrolled deposition variables (i.e., target conditioning) on the tribological performance.

MoS2↗

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